layer_zero_padding_1d
Zero-padding layer for 1D input (e.g. temporal sequence).
Description
Zero-padding layer for 1D input (e.g. temporal sequence).
Usage
layer_zero_padding_1d(
object,
padding = 1L,
batch_size = NULL,
name = NULL,
trainable = NULL,
weights = NULL
) Arguments
| Arguments | Description |
|---|---|
| object | What to compose the new Layer instance with. Typically a Sequential model or a Tensor (e.g., as returned by layer_input()). The return value depends on object. If object is: - missing or NULL, the Layer instance is returned. - a Sequential model, the model with an additional layer is returned. - a Tensor, the output tensor from layer_instance(object) is returned. |
| padding | int, or list of int (length 2) - If int: How many zeros to add at the beginning and end of the padding dimension (axis 1). - If list of int (length 2): How many zeros to add at the beginning and at the end of the padding dimension ( (left_pad, right_pad)). |
| batch_size | Fixed batch size for layer |
| name | An optional name string for the layer. Should be unique in a model (do not reuse the same name twice). It will be autogenerated if it isn’t provided. |
| trainable | Whether the layer weights will be updated during training. |
| weights | Initial weights for layer. |
Section
Input shape
3D tensor with shape (batch, axis_to_pad, features)
Output shape
3D tensor with shape (batch, padded_axis, features)
See Also
Other convolutional layers: layer_conv_1d_transpose(), layer_conv_1d(), layer_conv_2d_transpose(), layer_conv_2d(), layer_conv_3d_transpose(), layer_conv_3d(), layer_conv_lstm_2d(), layer_cropping_1d(), layer_cropping_2d(), layer_cropping_3d(), layer_depthwise_conv_1d(), layer_depthwise_conv_2d(), layer_separable_conv_1d(), layer_separable_conv_2d(), layer_upsampling_1d(), layer_upsampling_2d(), layer_upsampling_3d(), layer_zero_padding_2d(), layer_zero_padding_3d()